Exploring association and forecasting of evapotranspiration based on meteorological factors over megacity Lahore (Pakistan) and central place of Indo-Gangetic Basin

Umra Waris (), Saira Sarif () and Syeda Adila Batool ()
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Umra Waris: University of Management and Technology
Saira Sarif: University of Management and Technology
Syeda Adila Batool: University of the Punjab

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2024, vol. 26, issue 8, No 45, 20255-20277

Abstract: Abstract Any change in a meteorological variable can affect an environmental element’s evapotranspiration over time. This paper studies the dynamic causal relationships between evapotranspiration and meteorological parameters, which have long-term equilibrium relationships in Lahore, Pakistan, during the period from October 2004 to March 2020. The Augmented Dicky Fuller test reveals that the ARDL Approach to Cointegration is used for forecasting ET (kg m−2 s−1). The results depicted that geopotential height, surface air temperature, relative humidity at the surface, surface wind speed, tropopause height, surface skin temperature, and water vapor mass mixing ratio have a statistically significant long-run relationship with evapotranspiration. The results also revealed that cloud fraction, relative humidity at the surface, surface air temperature, total surface precipitation, water vapor mass mixing ratio, and tropopause height have a statistically significant short-run relationship with evapotranspiration. The $${\mathrm{CF}}_{(\mathrm{t}-1)}$$ CF ( t - 1 ) has the strongest effect on ET (kg m−2 s−1) in the short and long run. Speed of adjustment ( $${\mathrm{ECT}}_{\mathrm{t}-1}$$ ECT t - 1 ) shows a highly significant and negative relation, which indicates that after a 1 unit increase in the period, evapotranspiration (kg m−2 s−1) will go toward long-run equilibrium with a rate of 66.4%. The forecasted evapotranspiration time plot shows a long-term trend with seasonal components from April 2020 to March 2025.

Keywords: Evapotranspiration; Meteorological factors; Auto-regressive distributed lag (ARDL); Forecasting (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10668-023-03471-y

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